{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Nothing to be done\n",
      "INFO: METADATA is out-of-date — you may not have the latest version of DataFrames\n",
      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n",
      "INFO: Nothing to be done\n",
      "INFO: METADATA is out-of-date — you may not have the latest version of Gadfly\n",
      "INFO: Use `Pkg.update()` to get the latest versions of your packages\n"
     ]
    }
   ],
   "source": [
    "Pkg.add(\"DataFrames\")\n",
    "Pkg.add(\"Gadfly\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cd(\"/Users/utensil/experiments\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Cloning into 'julia'...\n"
     ]
    }
   ],
   "source": [
    "run(`git clone https://github.com/JuliaLang/julia.git`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cd(\"julia/test/perf/micro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "run(pipeline(`python perf.py`, stdout=\"py.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "run(pipeline(`julia perf.jl`, stdout=\"jl.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "载入需要的程辑包：compiler\n"
     ]
    }
   ],
   "source": [
    "run(pipeline(`r --vanilla --slave -f perf.R`, stdout=\"r.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "run(pipeline(`cat py.csv r.csv`, stdout=\"benchmarks.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "using DataFrames\n",
    "using Gadfly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><tr><th></th><th>language</th><th>benchmark</th><th>min</th><th>max</th><th>mean_time</th><th>std</th></tr><tr><th>1</th><td>julia</td><td>fib</td><td>0.056615</td><td>12.929825</td><td>0.06721</td><td>0.095576</td></tr><tr><th>2</th><td>julia</td><td>parse_int</td><td>0.184276</td><td>14.152507</td><td>0.240393</td><td>0.233401</td></tr><tr><th>3</th><td>julia</td><td>mandel</td><td>0.207146</td><td>15.422047</td><td>0.254343</td><td>0.232392</td></tr><tr><th>4</th><td>julia</td><td>quicksort</td><td>0.37266</td><td>4.646582</td><td>0.442788</td><td>0.085605</td></tr><tr><th>5</th><td>julia</td><td>pi_sum</td><td>23.337202</td><td>40.237361</td><td>26.38479</td><td>2.331499</td></tr><tr><th>6</th><td>julia</td><td>rand_mat_stat</td><td>20.954935</td><td>58.0542</td><td>24.982474</td><td>5.086046</td></tr><tr><th>7</th><td>julia</td><td>rand_mat_mul</td><td>36.421051</td><td>49.189161</td><td>39.883087</td><td>3.066839</td></tr><tr><th>8</th><td>julia</td><td>printfd</td><td>25.061242</td><td>34.104159</td><td>27.590273</td><td>1.608627</td></tr></table>"
      ],
      "text/plain": [
       "8x6 DataFrames.DataFrame\n",
       "│ Row │ language │ benchmark       │ min      │ max     │ mean_time │ std      │\n",
       "┝━━━━━┿━━━━━━━━━━┿━━━━━━━━━━━━━━━━━┿━━━━━━━━━━┿━━━━━━━━━┿━━━━━━━━━━━┿━━━━━━━━━━┥\n",
       "│ 1   │ \"julia\"  │ \"fib\"           │ 0.056615 │ 12.9298 │ 0.06721   │ 0.095576 │\n",
       "│ 2   │ \"julia\"  │ \"parse_int\"     │ 0.184276 │ 14.1525 │ 0.240393  │ 0.233401 │\n",
       "│ 3   │ \"julia\"  │ \"mandel\"        │ 0.207146 │ 15.422  │ 0.254343  │ 0.232392 │\n",
       "│ 4   │ \"julia\"  │ \"quicksort\"     │ 0.37266  │ 4.64658 │ 0.442788  │ 0.085605 │\n",
       "│ 5   │ \"julia\"  │ \"pi_sum\"        │ 23.3372  │ 40.2374 │ 26.3848   │ 2.3315   │\n",
       "│ 6   │ \"julia\"  │ \"rand_mat_stat\" │ 20.9549  │ 58.0542 │ 24.9825   │ 5.08605  │\n",
       "│ 7   │ \"julia\"  │ \"rand_mat_mul\"  │ 36.4211  │ 49.1892 │ 39.8831   │ 3.06684  │\n",
       "│ 8   │ \"julia\"  │ \"printfd\"       │ 25.0612  │ 34.1042 │ 27.5903   │ 1.60863  │"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jl_data = readtable(\"jl.csv\", header=false, names=[:language, :benchmark, :min, :max, :mean_time, :std])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><tr><th></th><th>language</th><th>benchmark</th><th>mean_time</th></tr><tr><th>1</th><td>python</td><td>fib</td><td>2.87795066833</td></tr><tr><th>2</th><td>python</td><td>parse_int</td><td>2.0809173584</td></tr><tr><th>3</th><td>python</td><td>mandel</td><td>3.95393371582</td></tr><tr><th>4</th><td>python</td><td>quicksort</td><td>14.358997345</td></tr><tr><th>5</th><td>python</td><td>pi_sum</td><td>652.050018311</td></tr><tr><th>6</th><td>python</td><td>rand_mat_stat</td><td>125.365018845</td></tr><tr><th>7</th><td>python</td><td>rand_mat_mul</td><td>66.064119339</td></tr><tr><th>8</th><td>r</td><td>fib</td><td>16.0</td></tr><tr><th>9</th><td>r</td><td>parse_int</td><td>4.0</td></tr><tr><th>10</th><td>r</td><td>quicksort</td><td>93.0</td></tr><tr><th>11</th><td>r</td><td>mandel</td><td>12.0</td></tr><tr><th>12</th><td>r</td><td>pi_sum</td><td>332.0</td></tr><tr><th>13</th><td>r</td><td>rand_mat_stat</td><td>86.0</td></tr><tr><th>14</th><td>r</td><td>rand_mat_mul</td><td>137.0</td></tr></table>"
      ],
      "text/plain": [
       "14x3 DataFrames.DataFrame\n",
       "│ Row │ language │ benchmark       │ mean_time │\n",
       "┝━━━━━┿━━━━━━━━━━┿━━━━━━━━━━━━━━━━━┿━━━━━━━━━━━┥\n",
       "│ 1   │ \"python\" │ \"fib\"           │ 2.87795   │\n",
       "│ 2   │ \"python\" │ \"parse_int\"     │ 2.08092   │\n",
       "│ 3   │ \"python\" │ \"mandel\"        │ 3.95393   │\n",
       "│ 4   │ \"python\" │ \"quicksort\"     │ 14.359    │\n",
       "│ 5   │ \"python\" │ \"pi_sum\"        │ 652.05    │\n",
       "│ 6   │ \"python\" │ \"rand_mat_stat\" │ 125.365   │\n",
       "│ 7   │ \"python\" │ \"rand_mat_mul\"  │ 66.0641   │\n",
       "│ 8   │ \"r\"      │ \"fib\"           │ 16.0      │\n",
       "│ 9   │ \"r\"      │ \"parse_int\"     │ 4.0       │\n",
       "│ 10  │ \"r\"      │ \"quicksort\"     │ 93.0      │\n",
       "│ 11  │ \"r\"      │ \"mandel\"        │ 12.0      │\n",
       "│ 12  │ \"r\"      │ \"pi_sum\"        │ 332.0     │\n",
       "│ 13  │ \"r\"      │ \"rand_mat_stat\" │ 86.0      │\n",
       "│ 14  │ \"r\"      │ \"rand_mat_mul\"  │ 137.0     │"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "benchmarks = readtable(\"benchmarks.csv\", header=false, names=[:language, :benchmark, :mean_time])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><tr><th></th><th>language</th><th>benchmark</th><th>mean_time</th></tr><tr><th>1</th><td>julia</td><td>fib</td><td>0.06721</td></tr><tr><th>2</th><td>julia</td><td>parse_int</td><td>0.240393</td></tr><tr><th>3</th><td>julia</td><td>mandel</td><td>0.254343</td></tr><tr><th>4</th><td>julia</td><td>quicksort</td><td>0.442788</td></tr><tr><th>5</th><td>julia</td><td>pi_sum</td><td>26.38479</td></tr><tr><th>6</th><td>julia</td><td>rand_mat_stat</td><td>24.982474</td></tr><tr><th>7</th><td>julia</td><td>rand_mat_mul</td><td>39.883087</td></tr><tr><th>8</th><td>julia</td><td>printfd</td><td>27.590273</td></tr></table>"
      ],
      "text/plain": [
       "8x3 DataFrames.DataFrame\n",
       "│ Row │ language │ benchmark       │ mean_time │\n",
       "┝━━━━━┿━━━━━━━━━━┿━━━━━━━━━━━━━━━━━┿━━━━━━━━━━━┥\n",
       "│ 1   │ \"julia\"  │ \"fib\"           │ 0.06721   │\n",
       "│ 2   │ \"julia\"  │ \"parse_int\"     │ 0.240393  │\n",
       "│ 3   │ \"julia\"  │ \"mandel\"        │ 0.254343  │\n",
       "│ 4   │ \"julia\"  │ \"quicksort\"     │ 0.442788  │\n",
       "│ 5   │ \"julia\"  │ \"pi_sum\"        │ 26.3848   │\n",
       "│ 6   │ \"julia\"  │ \"rand_mat_stat\" │ 24.9825   │\n",
       "│ 7   │ \"julia\"  │ \"rand_mat_mul\"  │ 39.8831   │\n",
       "│ 8   │ \"julia\"  │ \"printfd\"       │ 27.5903   │"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jl_benchmarks = jl_data[:, [:language, :benchmark, :mean_time]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><tr><th></th><th>language</th><th>benchmark</th><th>mean_time</th></tr><tr><th>1</th><td>python</td><td>fib</td><td>2.87795066833</td></tr><tr><th>2</th><td>python</td><td>parse_int</td><td>2.0809173584</td></tr><tr><th>3</th><td>python</td><td>mandel</td><td>3.95393371582</td></tr><tr><th>4</th><td>python</td><td>quicksort</td><td>14.358997345</td></tr><tr><th>5</th><td>python</td><td>pi_sum</td><td>652.050018311</td></tr><tr><th>6</th><td>python</td><td>rand_mat_stat</td><td>125.365018845</td></tr><tr><th>7</th><td>python</td><td>rand_mat_mul</td><td>66.064119339</td></tr><tr><th>8</th><td>r</td><td>fib</td><td>16.0</td></tr><tr><th>9</th><td>r</td><td>parse_int</td><td>4.0</td></tr><tr><th>10</th><td>r</td><td>quicksort</td><td>93.0</td></tr><tr><th>11</th><td>r</td><td>mandel</td><td>12.0</td></tr><tr><th>12</th><td>r</td><td>pi_sum</td><td>332.0</td></tr><tr><th>13</th><td>r</td><td>rand_mat_stat</td><td>86.0</td></tr><tr><th>14</th><td>r</td><td>rand_mat_mul</td><td>137.0</td></tr><tr><th>15</th><td>julia</td><td>fib</td><td>0.06721</td></tr><tr><th>16</th><td>julia</td><td>parse_int</td><td>0.240393</td></tr><tr><th>17</th><td>julia</td><td>mandel</td><td>0.254343</td></tr><tr><th>18</th><td>julia</td><td>quicksort</td><td>0.442788</td></tr><tr><th>19</th><td>julia</td><td>pi_sum</td><td>26.38479</td></tr><tr><th>20</th><td>julia</td><td>rand_mat_stat</td><td>24.982474</td></tr><tr><th>21</th><td>julia</td><td>rand_mat_mul</td><td>39.883087</td></tr><tr><th>22</th><td>julia</td><td>printfd</td><td>27.590273</td></tr></table>"
      ],
      "text/plain": [
       "22x3 DataFrames.DataFrame\n",
       "│ Row │ language │ benchmark       │ mean_time │\n",
       "┝━━━━━┿━━━━━━━━━━┿━━━━━━━━━━━━━━━━━┿━━━━━━━━━━━┥\n",
       "│ 1   │ \"python\" │ \"fib\"           │ 2.87795   │\n",
       "│ 2   │ \"python\" │ \"parse_int\"     │ 2.08092   │\n",
       "│ 3   │ \"python\" │ \"mandel\"        │ 3.95393   │\n",
       "│ 4   │ \"python\" │ \"quicksort\"     │ 14.359    │\n",
       "│ 5   │ \"python\" │ \"pi_sum\"        │ 652.05    │\n",
       "│ 6   │ \"python\" │ \"rand_mat_stat\" │ 125.365   │\n",
       "│ 7   │ \"python\" │ \"rand_mat_mul\"  │ 66.0641   │\n",
       "│ 8   │ \"r\"      │ \"fib\"           │ 16.0      │\n",
       "│ 9   │ \"r\"      │ \"parse_int\"     │ 4.0       │\n",
       "│ 10  │ \"r\"      │ \"quicksort\"     │ 93.0      │\n",
       "│ 11  │ \"r\"      │ \"mandel\"        │ 12.0      │\n",
       "│ 12  │ \"r\"      │ \"pi_sum\"        │ 332.0     │\n",
       "│ 13  │ \"r\"      │ \"rand_mat_stat\" │ 86.0      │\n",
       "│ 14  │ \"r\"      │ \"rand_mat_mul\"  │ 137.0     │\n",
       "│ 15  │ \"julia\"  │ \"fib\"           │ 0.06721   │\n",
       "│ 16  │ \"julia\"  │ \"parse_int\"     │ 0.240393  │\n",
       "│ 17  │ \"julia\"  │ \"mandel\"        │ 0.254343  │\n",
       "│ 18  │ \"julia\"  │ \"quicksort\"     │ 0.442788  │\n",
       "│ 19  │ \"julia\"  │ \"pi_sum\"        │ 26.3848   │\n",
       "│ 20  │ \"julia\"  │ \"rand_mat_stat\" │ 24.9825   │\n",
       "│ 21  │ \"julia\"  │ \"rand_mat_mul\"  │ 39.8831   │\n",
       "│ 22  │ \"julia\"  │ \"printfd\"       │ 27.5903   │"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "benchmarks = [benchmarks; jl_benchmarks]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "p = plot(benchmarks,\n",
    "    x = :language,\n",
    "    y = :mean_time,\n",
    "    color = :benchmark,\n",
    "    Scale.y_log10,\n",
    "    Guide.ylabel(nothing),\n",
    "    Guide.xlabel(nothing),\n",
    "    Theme(\n",
    "        default_point_size = 1mm,\n",
    "        guide_title_position = :left,\n",
    "        colorkey_swatch_shape = :circle,\n",
    "        minor_label_font = \"Georgia\",\n",
    "        major_label_font = \"Georgia\",\n",
    "    ),\n",
    ")\n",
    "draw(SVG(8inch,8inch/golden), p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "Compose.SVG(203.2mm,125.58450651397862mm,IOBuffer(data=UInt8[...], readable=true, writable=true, seekable=true, append=false, size=8429, maxsize=Inf, ptr=8430, mark=-1),nothing,\"img-6466a421\",0,Compose.SVGPropertyFrame[],Dict{Type{T},Union{Compose.Property{P<:Compose.PropertyPrimitive},Void}}(Compose.Property{Compose.JSCallPrimitive}=>nothing,Compose.Property{Compose.SVGClassPrimitive}=>nothing,Compose.Property{Compose.StrokePrimitive}=>nothing,Compose.Property{Compose.FillPrimitive}=>nothing),Dict{Compose.ClipPrimitive{P<:NTuple{N,Measures.Measure}},ASCIIString}(Compose.ClipPrimitive{Tuple{Measures.Length{:mm,Float64},Measures.Length{:mm,Float64}}}([(11.699999999999989mm,5.0mm),(177.36666666666665mm,5.0mm),(177.36666666666665mm,115.9511731806453mm),(11.699999999999989mm,115.9511731806453mm)])=>\"img-6466a421-25\"),Tuple{Compose.FormPrimitive,ASCIIString}[(Compose.CirclePrimitive{Tuple{Measures.Length{:mm,Float64},Measures.Length{:mm,Float64}},Measures.Length{:mm,Float64}}((0.0mm,0.0mm),0.9066666666666667mm),\"img-6466a421-14\"),(Compose.CirclePrimitive{Tuple{Measures.Length{:mm,Float64},Measures.Length{:mm,Float64}},Measures.Length{:mm,Float64}}((0.0mm,0.0mm),1.0mm),\"img-6466a421-41\")],Set{AbstractString}(),true,false,nothing,true,\"img-6466a421-71\",false,71,AbstractString[\"/Users/utensil/.julia/v0.4/Gadfly/src/gadfly.js\"],Tuple{AbstractString,AbstractString}[(\"Snap.svg\",\"Snap\"),(\"Gadfly\",\"Gadfly\")],AbstractString[\"fig.select(\\\"#img-6466a421-3\\\")\\n   .drag(function() {}, function() {}, function() {});\",\"fig.select(\\\"#img-6466a421-5\\\")\\n   .data(\\\"color_class\\\", \\\"color_fib\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-6\\\")\\n   .data(\\\"color_class\\\", \\\"color_parse_int\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-7\\\")\\n   .data(\\\"color_class\\\", \\\"color_mandel\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-8\\\")\\n   .data(\\\"color_class\\\", \\\"color_quicksort\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-9\\\")\\n   .data(\\\"color_class\\\", \\\"color_pi_sum\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-10\\\")\\n   .data(\\\"color_class\\\", \\\"color_rand_mat_stat\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-11\\\")\\n   .data(\\\"color_class\\\", \\\"color_rand_mat_mul\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-12\\\")\\n   .data(\\\"color_class\\\", \\\"color_printfd\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-15\\\")\\n   .data(\\\"color_class\\\", \\\"color_fib\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-16\\\")\\n   .data(\\\"color_class\\\", \\\"color_parse_int\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-17\\\")\\n   .data(\\\"color_class\\\", \\\"color_mandel\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-18\\\")\\n   .data(\\\"color_class\\\", \\\"color_quicksort\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-19\\\")\\n   .data(\\\"color_class\\\", \\\"color_pi_sum\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-20\\\")\\n   .data(\\\"color_class\\\", \\\"color_rand_mat_stat\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-21\\\")\\n   .data(\\\"color_class\\\", \\\"color_rand_mat_mul\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-22\\\")\\n   .data(\\\"color_class\\\", \\\"color_printfd\\\")\\n.click(Gadfly.colorkey_swatch_click)\\n;\",\"fig.select(\\\"#img-6466a421-26\\\")\\n   .init_gadfly();\"],false,:none)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = plot(benchmarks,\n",
    "    x = :language,\n",
    "    y = :mean_time,\n",
    "    color = :benchmark,\n",
    "    Scale.y_continuous,\n",
    "    Guide.ylabel(nothing),\n",
    "    Guide.xlabel(nothing),\n",
    "    Theme(\n",
    "        default_point_size = 1mm,\n",
    "        guide_title_position = :left,\n",
    "        colorkey_swatch_shape = :circle,\n",
    "        minor_label_font = \"Georgia\",\n",
    "        major_label_font = \"Georgia\",\n",
    "    ),\n",
    ")\n",
    "draw(SVG(8inch,8inch/golden), p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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